Adoption is as old as recorded history. It was practiced by the
ancient Egyptians, Greeks, and Romans. Technically, adoption is a legal
procedure by which a couple, or, less commonly, an individual, takes
someone else's child into their family and raises it as their own.
The child may be unrelated to either adoptive parent, but is often the
child of one member of the couple or related in some other way to the
adoptive parents. Adoption severs all legal ties between the birth
parents and the child and replaces them by a legal relationship between
the child and the adoptive parents. In most cases of adoption, the birth
parents voluntarily surrender their parental rights so that an adoption
can take place.

It seems highly likely that the U.S. Supreme Court will allow further
restrictions on the availability of abortion. As a consequence,
considerable attention is certain to be focused on the adoption option
and its social implications. Prior to 1970, fertility behavior was
little studied by economists, partly because it was thought that the
determinants were largely noneconomic. During the past two decades,
however, economists using a choice-theoretic framework have examined a
variety of fertility issues such as marriage (Becker |1974~),
procreation and children (DeTray |1973~), birth control (Willis |1973~),
and abortion (Leibowitz, Eisen, and Chow |1986~). Surprisingly, no
economic research exists on the issue of adoption, despite the fact that
it represents a natural extension of the traditional theory of consumer
choice. Most adoption research focuses on sociological issues such as
infertility or adoption procedures. This paper empirically estimates the
supply of adoptions using the decision-making economic framework of
completed fertility developed by Becker |1960~ and extended by Michael
|1973~. I believe their model's determinants of desired fertility
and family size will also be significant in explaining a
household's decision to give up a child for adoption. Section II
outlines the adoption model and relates it to the economic theory of
desired fertility and family size. The third and fourth sections discuss
the empirical estimates of the adoption model. The fifth section
examines the impact of various state regulations on the adoption
decision, and the last section discusses public and social implications
of the empirical results.

II. THE ADOPTION MODEL

Michael argues that households' decisions concerning desired
family size and the timing of childbearing can be explained in terms of
a household production function. Michael's model is based on a
comparison of the benefits and costs from an additional child over time.
His theory of completed fertility purports to be over a household's
full reproductive age span, but it is in actuality a period by period
analysis. Households are myopic in that, although they consider the
future costs and benefits of a child, an independent decision is made in
each period regarding whether to have a child. A household's
optimal family size may be, for example, two children. But if when the
first child is conceived the household perceives the timing of the birth
as undesirable, then, at that point in time, the net benefit from the
additional child is negative. The consequence is that the child is
"unwanted," and the household will take steps to reduce the
discrepancy between the desired and actual stock of children.

One possible solution is an adoption. Once a child is born, a
household has two choices: keep the child or put it up for adoption.
Michael's framework implies that the likelihood that a household
will place a child for adoption is positively related to the (negative)
discrepancy between the household's desired and actual stock of
children at that time. The factors affecting a household's desired
family size--income, time values, relative productivities, and revealed
tastes--are reflected in the discrepancy between the desired and actual
stock of children. These factors, which determine the desirability of
childrearing, should also figure in the adoption decision. The adoption
supply equation is modeled in terms of these factors.

The dependent variable is the adoption rate (the number of unrelated
adoptions of healthy infants as a percentage of live births) for women
of childbearing age (defined as fifteen to forty-four years old) in
state i during the 1982 calendar year. The dependent variable examines
only healthy infants placed for adoption and excludes the adoptions of
children with special needs or by foster parents. It is generally agreed
that there is a severe shortage of adoptable healthy infants. The 1982
National Survey of Family Growth estimated that there were approximately
one million childless couples, who constitute the group most likely to
consider an adoption. However, in 1982 there were less than eighteen
thousand healthy infants available for adoption. Consequently, the
market for adoptable infants has chronic excess demand and equilibrium
is reached solely on the basis of the supply curve. Any exogenous change
will shift the adoption supply curve, and a new equilibrium will be
achieved at essentially the same price, but at a different level of
output (adoptable infants). In effect, the paper examines how various
independent variables shift the supply of adoptable infants in the face
of chronic excess demand.(1)

The independent variables in equation (1) are restricted principally
to women rather than households since it is women who bear the children
and who primarily incur the explicit and implicit costs of
childrearing.(2) Furthermore, through a succession of opinions, the U.S.
Supreme Court has ruled that for unmarried couples the biological mother
has primary parental decision rights as long as the biological
father's due process is recognized.

The female income variable is the average income of women aged
fifteen to forty-four, and the male income variable is the average
income of males. The sum of these measures the budget constraint on a
household's ability to purchase goods and services. Changes in a
woman's income will affect the adoption decision in two ways, with
opposite effects. A rise in a woman's income increases the
opportunity cost of childrearing in terms of the earnings that a woman
must forego if she leaves the workforce to raise a child. This will,
therefore, tend to affect the adoption option positively (substitution
effect). However, the increase in a woman's income also relaxes the
budget constraint (income effect). The income effect on the adoption
decision may be either positive or negative. Becker suggests two
possible reasons why the income effect may be negative. First, the
probability of an unwanted child may fall because the effectiveness of
contraceptive methods may increase with income. Second, households may
increase the amount spent per child, substituting an increase in the
quality of children for the quantity of children. Thus the impact of a
change in female income on the adoption decision depends on the relative
magnitudes of the substitution and income effects, and the predicted
effect is ambiguous. Similarly, the effect of male income on the
adoption decision is uncertain.(3) The empirical research on whether the
income elasticity of demand for quantity of children is positive or
negative is contradictory.(4)

Another determinant of the adoption rate is a woman's marital
status. It is hypothesized that single women will be more likely to
place a child for adoption because the private and social costs of an
additional child are greater for them than for married women. Married
women, who are more likely to already have at least one child, benefit
from economies of scale and greater experience in childrearing, and have
a spouse to help them, and so are likely to have lower outlays for
childrearing than single women.(5) The social cost of a child is greater
for unmarried women than married women due to the stigma usually
associated with unmarried motherhood. The predicted effect of the
percentage of women aged fifteen to forty-four who are single is
positive.

Also relevant in a woman's adoption decision is her labor force
status. Women in the labor force should be more likely to place a child
for adoption because of the greater cost incurred as a result of the
loss in competitive skills and on-the-job training and experience should
they leave the labor force to raise a child. However, a number of
researchers have found that working women are much more likely than
nonworking women to have planned both the timing of childbirth and the
number of children they want, and thus are less likely to have unwanted
births.(6) Accordingly, if one accepts both possibilities as potential
determinants of the adoption rate, then the predicted effect of the
variable the labor force participation rate of women aged fifteen to
forty-four is uncertain.(7)

Another determinant of the adoption rate is the unemployment rate of
fertile women. Economic theory suggests that as the unemployment rate
rises, the value of a woman's time falls, and, concomitantly, so do
the costs of rearing an additional child. This implies that the adoption
rate will fall. However, this assumes that a woman's labor supply
is procyclical. It is possible that a woman's labor supply is
countercyclical (the added worker effect) to reduce the variability of
household income.(8) If this were the case, then as the unemployment
rate rises the value of a woman's time and costs of rearing an
additional child would rise and the adoption rate would increase. Thus
the expected sign of the unemployment variable is an empirical question.

Michael suggests that education may have two separate and opposite
effects on a household's desired fertility objective. On the one
hand, education may reduce the likelihood of adoption since the more
educated the woman the less likely she will have unwanted births (both
in timing and number) because of greater knowledge about and use of
effective birth control techniques. It is also more likely the household
will be induced to substitute toward quality and away from quantity of
children. On the other hand, education, through its effects on an
individual's human capital, may also increase the likelihood of
adoption since it raises the opportunity cost of a household's time
and, since children are time-intensive relative to other goods, increase
the relative price of an additional child (Willis |1973~). The education
variable is the percentage of women aged fifteen to forty-four in each
state who have completed twelve years of school, and its expected effect
is indeterminate.

The adoption rate should also be dependent upon the level of
financial assistance available from social welfare programs. Ellwood and
Bane |1985~ and Garfinkel and McLanahan |1986~ found that welfare
programs did not influence the childbearing decisions of women but did
have an impact on living arrangements (i.e., female-headed households).
Welfare payments may enable a woman in poverty to keep her baby since
the level of financial assistance increases for each additional child.
Aid to Families with Dependent Children is the guaranteed payment for
one child in each state. I hypothesize that it will have a negative
influence on the adoption rate.

The last two variables control for demographic differences in tastes
for adoption. Religion is a powerful moral and social force in household
choices. Research by Goldscheider and Mosher |1991~ found that Christian
fundamentalists, as compared to other religious groups, were less likely
to use contraception and those using contraceptives were more likely to
use a relatively ineffective method. Also, fundamentalism has been found
to have a significant effect on sexual morality and abortion.(9) This
suggests that fundamentalist women may also be more likely to have more
unplanned or unwanted pregnancies. If fundamentalist women are more
likely to value large families or less likely to conceive out of
wedlock, then they would be more likely to keep the child.
Alternatively, fundamentalist women with unwanted pregnancies might
choose the adoption option in order to avoid their church's and
community's moral sanctions against abortion. The fundamentalism
variable is the percentage of each state's population that claims
membership in a denomination that professes a belief in the literal
interpretation of the Bible.

The other taste variable is the percentage of fertile women in each
state who are black. Sociologists and demographers (e.g., Westoff and
Ryder |1977~) have suggested that black women practice less family
planning and have more unwanted births than white women, which would
imply a higher adoption rate for black women. However, black women may
be reluctant to put a child up for adoption because the available pool
of black adoptive families is smaller than for white families since
black women are less likely than white women to have ever married
(National Committee for Adoption |1985~).(10)

III. THE EMPIRICAL RESULTS

The adoption equation was first estimated using ordinary least
squares. A plot of the residuals against the estimated values of the
dependent variable suggested the presence of heteroscedasticity.(11)
Using the procedure proposed by Glejser, I determined that the variance
of the residuals decreased with the square of the number of black female
teenagers in each state.(12) In order to achieve efficient estimates, I
reestimated equation (1) using generalized least squares.(13) The
generalized least squares estimates of equation (1) appear in Table I,
column 1. Female income is positive, but not statistically significantly
different from zero. This does not mean that a woman's income is
not a determinant of her placing a child for adoption. Rather it
suggests that the substitution effect was offset by an equal but
opposite pure income effect that resulted in female income being
statistically and numerically insignificant.(14) Similarly, male income
is negative, but not a significant determinant of the adoption
decision.(15)

TABULAR DATA OMITTED

The marital status variable is significantly positive, which is
consistent with the hypothesis that unmarried women, due to their higher
private and social costs, are more likely to place a child up for
adoption. The variable for labor force participation is also
significantly negative. This result is consistent with previous research
that found that working women are less likely to have unwanted births
than nonworking women. The higher the level of Aid to Families with
Dependent Children the more likely women in poverty will keep an
additional child. The higher the unemployment rate the less likely women
are to put a child up for adoption, presumably because women's
labor supply is procyclical with a resultant lower opportunity cost of
childrearing. Fundamentalist women are found to be significantly more
likely to place a child for adoption. This finding is consistent with
the contention by sociologists that the social stigma of illegitimate
births to fundamentalist women and the religious prohibition of abortion
increase the likelihood of a child being given up for adoption. The
percentage of black women in the population of fertile women is found
not to be a significant determinant of the adoption rate. Black women
are not more or less likely to place a child for adoption.

One particularly interesting result was the finding that the
percentage of women who have completed high school has a statistically
significant positive effect on the adoption rate. There are several
possible, not necessarily competing, explanations consistent with this
finding. First, high school dropouts may be less likely to offer a child
for adoption because of a lower opportunity cost of childrearing.
Second, female high school dropouts are more likely to have grown up in
disadvantaged socioeconomic circumstances (broken families, on public
assistance, or mother was teenager at first birth) and as a consequence
may be less likely to consider the benefits of adoption.(16) Third,
women with at least a high school degree may be more motivated to avoid
unplanned births and childrearing because such an event would interfere
with their educational, occupational, and economic goals.(17)

To test for the robustness of the model, I reestimated equation (1)
with several other independent variables included. A regional dummy
variable equal to one for states in the West was added to equation (1)
to determine if there were regional differences in social mores or
attitudes regarding adoption. The western states variable was not
statistically significantly different from zero. A similar result was
obtained for states in the East. The percent of women of childbearing
age who are between the ages of 15-19, 15-17, and 18-19 was included
separately in equation (1) to test whether any of these age groups were
more likely to place a child for adoption. However, each variable was
found not to have a significant influence on the adoption rate. In all
the estimates, the coefficients of the other variables in the model
remained virtually identical to those previously reported.(18)

IV. ADOPTION AND ABORTION

The theoretical model of desired family size suggests that when
excess fertility occurs, a child is "unwanted" and a household
will attempt to reduce the discrepancy between actual and desired family
size at that time. I have focused on the decision by women to reduce the
discrepancy by placing the child for adoption. However, relative to
adoption, the method most frequently used to reduce unwanted births is
abortion.

It is of interest to empirically examine what impact the abortion
option has on the adoption decision.(19) In order to test this, equation
(1) was reestimated with the dependent variable redefined as the number
of unrelated adoptions of healthy infants as a percentage of pregnancies
of women of childbearing age in state i in 1982 (ADOPT/|PREG.sub.i~). In
addition to the independent variables already specified in equation (1),
two other independent variables were included. The price of abortions is
the average cost of an abortion in each state in 1982.(20) If abortion
is a substitute for adoption, then the predicted effect of the price of
an abortion is positive. In addition, in 1982 federal funding of
abortions through the Medicaid program was prohibited. However, fourteen
states continued to provide unrestricted funding of abortions through
state medicaid programs. Such expenditures represent a subsidy to
abortion and clearly will have a price effect. The effect is likely to
be particularly strong for young, unmarried, low-income women. For this
group of women the availability of state-funded abortions may be a more
important price determinant than the actual cost of an abortion. Thus
state funding of abortions, by reducing the cost of an abortion relative
to an adoption, would be expected to have a negative impact on the
adoption decision. The medicaid variable is a dummy variable equal to
one for those states that continued abortion funding. The empirical
results are given in Table I, column 2.

The estimated coefficients of the independent variables previously
reported remained virtually unchanged. The price of an abortion is
negative, but not statistically significantly different from zero. This
result suggests that abortions and adoptions are not substitutes. Even
though both methods reduce excess fertility, women with unwanted
pregnancies apparently do not perceive adoption and abortion as
equivalent options. The coefficient of the state medicaid funding
variable is negative and statistically significantly different from
zero. This result which in conjunction with the negative coefficient of
the Aid to Families with Dependent Children variable suggests that poor
women regard adoption as a less desirable alternative than keeping the
child or having an abortion.

The finding that the price of an abortion has no statistically
significant impact on the adoption option does not necessarily mean that
the availability of abortions has no effect on the supply of adoptive
children. A pregnant woman has three mutually exclusive options
available to her. She can have an abortion, bear the child and keep it,
or give it up for adoption. Thus a pregnant woman faces three
alternatives and must choose one of them. Such a choice model can be
estimated using the multinomial logit model. The advantage of this
direct approach is that the choice probabilities are dependent on
individual characteristics only.(21) The functional form of the multiple
logit model for the equation of particular interest is log(Prob
adopt/Prob abort) = f(X) where Prob adopt and Prob abort are the
proportion of pregnancies that result in an adoption or abortion,
respectively, and X is the vector of all the independent variables used
in the previously estimated equation in this section.(22) The estimated
parameters show the probability that an individual with a specified set
of personal characteristics will choose an adoption relative to an
abortion. The estimated coefficients are given in Table I, column 3.

Essentially, what these results show is that a single woman or a
woman in the labor force is more likely to chose an abortion relative to
adoption, whereas a fundamentalist woman is more likely to choose the
adoption option. The variable TABULAR DATA OMITTED of particular
interest, the price of an abortion, is negative, but not statistically
significantly different from zero. Again the empirical results suggest
that abortion availability has had very little effect on the supply of
adoptive children. The reason may be that women who obtain legal
abortions would undertake other alternatives if abortion was not legal.
Such possibilities include becoming a single parent, keeping the child
and marrying the father, or obtaining an illegal abortion.

V. THE IMPACT OF STATE REGULATIONS

Adoption in the United States is regulated by the states, subject to
state laws and under the jurisdiction of state courts. Of particular
interest is the impact various state regulations have on the supply of
adoptive children.

There are two types of adoptions: agency and private. All states
permit children to be placed for adoption by state social service
agencies or state-licensed adoptive agencies (e.g., United Way, Catholic
Services). Some states also allow private adoptions which are arranged
by prospective adoptive parents through intermediaries such as lawyers
or doctors. Many states prohibit private adoptions, arguing they
increase the possibility of extortion in unduly pressuring a mother to
surrender her child. Proponents argue that private adoptions facilitate
the adoption process by providing flexibility in finding adoptive
parents quicker and more efficiently in finding adoptive children. To
investigate the effect of private adoptions, I added a dummy variable
equal to one for states which allow private adoptions to equation (1).
The empirical results, which appear in Table II, column 1, show that
private adoptions have no statistically significant effect on the supply
of adoptive children. States which allow private adoptions do not have
more adoptive children.

Adoption procedures emphasize the confidentiality of the adoption
parties. There has been a strong tradition of protecting the privacy
rights of those involved in adoption. Virtually all states required that
adoption records be sealed. During the mid-1970s opposition mounted to
sealed adoption records. By 1980, because of pressure from adoptee
lobbying groups, a number of states enacted laws allowing adoptees
and/or biological parents to register their desire to meet as well as
laws that provided for contacting the biological parents in order to
obtain consent for a meeting. Of particular interest is whether allowing
adoption records to be opened deters placing a child for adoption. To
test this, I added a dummy variable equal to one for states which
mandate the confidentiality of adoption records to equation (1). The
empirical results from Table II, column 2 show that the confidential
records variable is not statistically significantly different from zero.
Keeping adoption records confidential does not foster the adoption
process, or conversely, allowing open adoption records does not inhibit
the supply of adoptive children.

Many states allow prospective adoptive parents to pay certain
expenses of the birth mother (e.g., medical, legal, and counseling
costs) presumably to encourage adoptions. Do such subsidies encourage
birth mothers to give up a child for adoption or are they irrelevant to
the adoption decision? To examine the effect of expense subsidization on
the adoption decision, a dummy variable equal to one for states that
permit the biological mother's expenses to be paid by the adoptive
parents was added to equation (1). The empirical results, from Table II,
column 3, find the expense variable is not statistically significantly
different from zero. Subsidization of the biological mother's
expenses by adoptive parents does not have any statistically significant
impact on the supply of adoptive children.

In order for an adoption to take place, consent of the biological
mother is required, however, do allow the birth mother time to revoke
her consent before she terminates her parental rights. An interesting
issue, particularly to adoptive parents, is whether the length of time
allowed for withdrawal of consent has any impact on the birth
mother's decision to give up a child for adoption. Are biological
mothers more likely to change their mind the longer the time period
allowed, or does the decision tend to be irrevocable? This question was
examined by adding the length of time a state allows for withdrawal of
consent to equation (1). Table II, column 4 shows that the time variable
was negative, but not statistically significantly different from zero. A
birth mother's decision to give up a child tends to be invariant to
the time period allowed for withdrawal of consent.(23)

I. CONCLUSION

Opponents of abortion have often argued that adoption is a viable
alternative if the U.S. Supreme Court were to prohibit legal abortions.
All abortions, however, would not be eliminated since there would still
be the possibility of obtaining an illegal abortion. Based on the
approximately 1,500,000 abortions done annually in the United States,
Medoff |1988~ estimated that if abortions were prohibited there would
still be between 600,000 and 900,000 illegal abortions performed
annually.

This study estimated the supply of adoptions. The results found that
the adoption rate was negatively related to a woman's participation
in the labor force, the size of Aid to Families with Dependent Children
payments, and the unemployment rate. Single mothers, fundamentalist
women, and a high school education were found to have a positive impact
on the adoption rate. The empirical results suggest that societal
changes and trends in women's attitudes, economic status, and
feminist views have caused adoption to be considered a less desirable
option than abortion or childrearing. Even if abortions were made
illegal, only a small number of women, those who could not obtain an
illegal abortion or who decided not to become single mothers, would
surrender their child for adoption. Furthermore, state regulations,
which presumably are designed to encourage the adoption option, are
found not to have any impact on the decision to relinquish a child.

MARSHALL H. MEDOFF Department of Economics, California State
University, Long Beach. Funding for this research was provided by
California State University, Long Beach through the Scholarly and
Creative Activity Program.

1. Unlike a conventional supply curve which shows at each price how
many units of output suppliers would be willing to offer for sale, the
adoption supply equation does not have a price variable which would
induce women to offer a child for sale since every state imposes
criminal penalties for child selling and/or child buying.

2. It might be argued that the independent variables should be
restricted to mothers of newborn infants rather than all fertile women.
There is no bias in the estimated coefficients since the factors
affecting a household's desired family size are the same for both
groups of women.

3. In 1982, approximately 82 percent of births were to married women.

4. For two viewpoints see Dooley |1982~ and Cain and Weininger
|1973~.

5. In 1980, 50.5 percent of all married women (spouse present) had at
least one child, versus 14.2 percent for unmarried women (U.S. Bureau of
the Census |1983~).

6. On this point see Westoff and Ryder |1972~ and Ward and Butz
|1980~.

7. It might be argued that income and labor force participation are
endogenous to fertility. However adoption is an ex post event--the
decision by a women to give up her child. Thus all the variables are
exogenous at the time of the adoption decision.

8. In 1982, two out of three unemployed persons lived in a household
with another working member. I am indebted to an anonymous referee for
suggesting this possible relationship.

9. See Jones |1983~ and Medoff |1989~.

10. The data on all economic variables were obtained from the U.S.
Bureau of the Census, State Reports, Detailed Characteristics |1983~.
The data on adoptions and adoption law were obtained from the National
Committee For Adoption, Adoption Factbook |1985~ and Sloan |1988~. The
data on religious affiliation was from the National Council of Churches
survey, Churches and Church Membership in the United States: 1980 (Quinn
|1982~). The mean and standard deviation (in parentheses) for the
dependent variable and independent variables in equation (1) are
|ADOPT.sup.s~: .61(.40); Female Income: 6407.3(936.34); Male Income:
14612.4(1767.7); Single: 34.16 (3.96); Labor Force Participation:
61.99(4.61); Unemployment: 7.63(1.93); Education: 71.88(4.39); Aid
Families Dependent Children: 255.42(104.61); Fundamentalism:
13.72(12.8); Black: 9.47(9.79).

11. A Goldfeld-Quandt procedure on equation (1) showed that the
calculated F-value exceeded the critical F-value at the .05 level of
significance and thus the null hypothesis of homoscedasticity was
rejected.

12. Sixteen states had a total population which was less than 3
percent black.

13. A complete description of the Glejser procedure and generalized
least squares estimation is detailed in Maddala |1984~.

14. Mincer |1963~ suggests that since a husband and wife's
earnings tend to be positively correlated, failure to account for this
influence biases downward estimates based on cross-sectional data of the
effect of income on fertility.

15. When the income variables were omitted from equation (1) the
empirical results were (absolute value of t-statistics in parentheses):

|ADOPT.sup.s~ = -5.3835 + .0346 Single (2.08) (1.97)

-.0018 Labor Force Participation (1.61)

-.0524 Unemployment + .0771 Education (2.43) (2.08)

-.0018 Aid Families Dependent Children (3.53)

+ .0118 Fundamentalism + .0016 Black (1.99) (.21)

The income variables were included in the estimation because of its
theoretical implications.

16. See Kalmuss, Namerow, and Cushman |1991~ for a discussion of this
issue.

17. Suggested by McLaughlin, Manninen, and Winges |1988~.

18. The complete empirical results are available upon request.

19. In 1989, the U.S. Supreme Court ruled that states could impose
some restrictions on abortions performed in the first twenty-four weeks.
Up until that time the Supreme Court had required all states to permit
abortion on demand through the second trimester (less than one percent
of all abortions occur in the third trimester). State laws mandating a
waiting period, spousal involvement, parental consent, or information
about other alternatives were not in effect during the 1982 period under
study either because such laws were not enforced or enjoined because of
court challenges or not yet enacted. Thus there did not exist any state
variance in abortion regulation in 1982.

20. All the information pertaining to abortions was obtained from the
Alan Guttmacher Institute which is the research institution affiliated
with Planned Parenthood. The information provided by the Guttmacher
Institute is from a yearly national survey, and its results are
acknowledged by the U.S. Department of Commerce in the Statistical
Abstract of the United States to be the most complete available.

21. See Judge et al. |1985~ chapter for a description of the
multinomial logit model.

22. A complete description of the multinomial logit model is
available in Judge et al. |1985~. The other estimated equation was
log(Prob childrear/Prob abort) = f(X). The complete empirical results
are available upon request.

23. The state regulation variables were also statistically
insignificant when any two, three or all of them were added to equation
(1). The state regulation variables were also found to be statistically
insignificant when the dependent variable was ADOPT/PREG. The complete
empirical results are available upon request.

Dooley, Martin D. "Labor Supply and Fertility of Married Women:
An Analysis with Grouped and Individual Data from the 1970 U.S.
Census." Journal of Human Resources, Fall 1982, 499-532.

Ellwood, David T., and Mary Jo Bane. "The Impact of AFDC on
Family Structure and Living Arrangements," in Research In Labor
Economics, edited by R. G. Ehrenberg. Greenwich, CT: JAI Press, 1985,
137-207.